The fuzzy systems handbook: a practitioner's guide to building, using, and maintaining fuzzy systems
The fuzzy systems handbook: a practitioner's guide to building, using, and maintaining fuzzy systems
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Fast and accurate text classification via multiple linear discriminant projections
The VLDB Journal — The International Journal on Very Large Data Bases
From Unstructured Data to Actionable Intelligence
IT Professional
Handbook on Ontologies
Mining Customer Feedbacks for Actionable Intelligence
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Exploiting probabilistic topic models to improve text categorization under class imbalance
Information Processing and Management: an International Journal
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Text analytics on consumer-generated content has gained significant momentum over last few years. A wide-range of text mining techniques has been proposed which can provide interesting insights about the text content. But, the challenge still exists in consuming the extracted information in form of actionable intelligence. Identifying actionable intelligence is difficult due to differences in consumer and business languages. Since feedbacks rarely talks of a single problem, determining the problems is also challenging. We propose a framework to address some of these challenges. Organizational websites or standard domain-ontologies are rich repositories of domain knowledge. The proposed method utilizes this knowledge to learn a discriminative classifier model for a domain using Fisher's discriminant metric. The consumer feedbacks are classified to different business categories using the learnt model. The output is further fed into a fuzzy reasoning unit where every feedback is assigned confidence values for each category. Initial experiments show that the proposed framework is capable of handling text feedbacks containing customer complaints in various domains.